I am a Postdoctoral Associate in the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work at MIT. I will start as an Assistant Professor in the Sociology Department at UC Berkeley in January 2027. Previously, I was a Postdoctoral Scholar in the Stone Program in Wealth Distribution, Inequality, and Social Policy at Harvard.

Primarily, I study the kinship networks that weave elites together. My research tracks the capture and circulation of resources through upper-class populations over time, with a particular focus on gender/sexuality, whiteness, wealth, and the United States.

Combining an array of qualitative and quantitative archival data, I have built the first-ever full kinship network of an upper class in a U.S. city, covering all elites in Dallas for its first 125 years (n = 20,342). I am currently building a second dataset covering all the millionaires and politicians in the United States during its first Gilded Age, along with all their mutual kin.

Using an iterative mixed-methods approach, I draw on these data to tackle classic topics in stratification, economic sociology, political sociology, and the social science of elites. My first paper using the Dallas data, “The Family Web,” co-won the 2025 Socio-Economic Review Best Paper Prize, and my dissertation won the 2024 Theda Skocpol Dissertation Award in Comparative-Historical Sociology. Another paper using the Dallas data, “Kinship Interlocks,” was recently published in American Sociological Review.

I received my Ph.D. in Sociology from Princeton University. My work has been supported by the Munich International Stone Center, the Harvard Stone Program, an American Sociological Association Doctoral Dissertation Research Improvement Grant (ASA DDRIG), a Mellon/ACLS Dissertation Completion Fellowship from the American Council of Learned Societies, and funding from multiple sources at Princeton, as well the Clements-DeGolyer Center at Southern Methodist University and the Portal to Texas History at the University of North Texas.